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Jill M. White, RN, PhD About the Author By Jill M. White, RN, PhD. From the School of Nursing, University of Wisconsin-Milwaukee, Milwaukee, Wis. This article originally appeared in the July 1999 issue of the American Journal of Critical Care, Vol 8, No. 4, pp.220-230. Each year 1.5 million persons in the United States experience acute myocardial infarction (AMI).1 AMI is accompanied by elevated anxiety levels, which in turn increase activity of the sympathetic nervous system. Compelling evidence indicates a relationship between action of the autonomic nervous system and sudden cardiac death.2-5 Specifically, activation of the parasympathetic division of the autonomic nervous system exerts a protective and antifibrillatory effect on the heart, and increased activity of the sympathetic division contributes to the onset of life-threatening cardiac dysrhythmias. When the activity of the sympathetic nervous system is increased, an additional stress is placed on an already compromised myocardium. This additional stress results in increases in heart rate, blood pressure, and corresponding myocardial oxygen requirements. These demands may have an adverse effect on patients’ prognosis and recovery during the acute recovery phase of myocardial infarction. Approaches aimed at reducing stress and anxiety, such as music therapy,6-12 biofeedback,13 and progressive muscle relaxation,9 are designed to elicit a psychophysiological relaxation response. Although many approaches have been reported, research on the effectiveness of these treatments is limited. One promising intervention is music therapy. Recognition of the therapeutic effects of music dates back to primitive humans, who believed that music had the power to free the body of “evil spirits.”14 Through the years, such prominent scholars as Plato and Pythagoras,15 Aristotle,16 and Nightingale17 have espoused the beneficial effects of music. Decades of research indicate that the most relaxing music has a tempo of approximately 60 beats per minute,16,18 is composed of predominantly low tones,19 and is largely stringed in composition, with minimal brass or percussion.16,18-20 The conceptual framework that guided the study reported in this article was based on research on stress and coping,21 the relaxation response,22-24 and music16,25-27 and on physiological theory28 (see Figure). Admission to a critical care unit after diagnosis of AMI exposes patients to multiple psychological and physiological stressors, including fear, noise, uncertainty, compromised coronary circulation, diminished myocardial oxygen supply, and pain. When a patient perceives these stressors as threatening to his/her integrity, a stress response ensues.21 x A stress response stimulates the release of epinephrine and norepinephrine, resulting in increases in heart rate, respiratory rate, arterial blood pressure, myocardial oxygen demand, and state anxiety levels. In addition, heart rate variability (HRV) is reduced. These adverse effects increase the chance of post-AMI complications, including episodes of sudden cardiac death. Benson et al24 suggest that the stress and relaxation responses are mutually exclusive events. Properly selected music can elicit a relaxation response in a number of ways. Music may act as a distraction and divert attention from the stressful stimuli,26 or it may act directly on the autonomic nervous system.16,25 Furthermore, music may summon memories of past experiences and associated emotional responses.27 When a relaxation response occurs, the stress response is interrupted and anxiety levels are decreased. Decreased anxiety is accompanied by increased vagal outflow and diminished activity of the sympathetic nervous system. Changes in heart rate, blood pressure, myocardial oxygen demand, and HRV are controlled primarily by the autonomic nervous system. Increased stimulation of the sympathetic nervous system reduces HRV and increases heart rate and force of cardiac contraction; increases in parasympathetic activity decrease heart rate and increase HRV. Increases in heart rate and force of cardiac contraction result in increased myocardial oxygen demand. Modulations in heart periods, or intervals between successive QRS complexes, originating from cyclical changes in control of the sinoatrial node by the autonomic nervous system are commonly referred to as HRV. Therefore, HRV analysis provides a means of assessing the rhythmical changes that occur in instantaneous heart rate (R-R intervals) in response to alterations in sympathovagal balance. Decreased HRV has been associated with increased risk after AMI28-30 and may be one of the best predictors of post-AMI mortality and morbidity.29,31-33 Several investigators6-12 have studied the effects of relaxing music on the anxiety that occurs after AMI. The most consistent finding is a reduction in anxiety levels after relaxing music sessions.6,10-12 Likewise, reductions in heart rate,9-12 respiratory rate,11 and systolic blood pressure12 and an increase in galvanic skin response9,12 have been observed. Results from these studies support the therapeutic benefits of relaxing music after AMI. However, to date, the effects of relaxing music on myocardial oxygen demand and HRV have not been investigated in patients with confirmed AMI. Moreover, the sustained effects of relaxing music have not been examined. Therefore, the purpose of this study was to examine the effects of selected relaxing music on heart rate, respiratory rate, systolic blood pressure, myocardial oxygen demand, HRV, and anxiety during the acute recovery phase of AMI. Specifically, I hypothesized that patients who listened to relaxing music would have greater reductions in heart rate, respiratory rate, systolic blood pressure, myocardial oxygen demand, and state anxiety and greater increases in high-frequency HRV than would participants who experienced quiet rest or “treatment as usual.” I anticipated that these changes would occur immediately and 1 hour after a 20-minute intervention. Method Sample and Setting Forty-five patients who had had an AMI during the previous 72 hours were recruited for participation in the study. All participants were residing in private rooms in intensive care units (ICUs) in 2 midwestern hospitals. Inclusion criteria for participation included (1) confirmed AMI within the previous 72 hours, (2) hemodynamic condition stable enough for participation as determined by the attending registered nurse, (3) alert and oriented, and (4) primary cardiac rhythm originating from the sinoatrial node. Diagnosis of AMI was confirmed by at least 2 of the following criteria: (1) ECG changes consistent with infarction, (2) elevated levels of creatine kinase–MB, or (3) elevated levels of troponin I. All potential subjects had been notified by their attending physician that they had experienced an AMI. Subjects who were receiving mechanical ventilation were excluded from participation in the study. Procedure Approval was obtained from the institutional review boards of all participating agencies. A repeated measures experimental design was used. Subjects were assigned randomly, 15 per group, to a 20-minute intervention of (1) music and a quiet, restful environment (experimental group); (2) a quiet, restful environment (attention group); or (3) treatment as usual (control group). The purpose and requirements of participation in the study were discussed with each potential participant, and informed consent was obtained. Participants were enrolled in the study between the hours of 9 and 11 am in order to minimize the effects of circadian variation of HRV. After informed consent was obtained, a 2-channel bipolar Holter recorder (Series 8500, Marquette Electronics Inc, Milwaukee, Wis) was attached to each participant. In order to control for postural influences on autonomic function, all physiological parameters were measured with subjects in a semi-Fowler’s position with the head of the bed raised approximately 45°. Demographic and 30 minutes of baseline HRV data were collected. After this 30-minute period, baseline physiological values were obtained. Subjects also were asked to complete the state part of the State-Trait Anxiety Inventory.34 Subjects in the experimental and attention groups were asked to void if necessary and to assume a comfortable position in bed. Then, lights were lowered, telephones unplugged, curtains drawn, and doors closed. Participants were advised to clear their minds and to allow their muscles to relax. Subjects in the experimental group used a CD minidisc player and headphones to listen to a 20-minute recording of investigator-selected classical music; subjects in the attention group were provided with 20 minutes of uninterrupted rest. The investigator remained outside the patients’ rooms to ensure that subjects were uninterrupted. During this 20-minute treatment period, subjects in the control group were engaged in activities as usual without intervention or environmental manipulation by the investigator. Immediately after the 20-minute intervention, physiological parameters were measured again, and subjects were asked to complete the state part of the State-Trait Anxiety Inventory again. This procedure for data collection was repeated 1 and 2 hours after the intervention. Electrocardiographic (ECG) data were recorded continuously during the 3-hour period. Holter recordings were marked by means of an event marker at data collection points to ensure that measurements of HRV corresponded to all other collected data. Instrumentation Heart Rate. Heart rate was determined by obtaining a hard copy of 1 full minute of ECG data. The morphology of each ECG complex was determined, and the frequency of occurrence for each category of ECG complex was determined. Heart rate was recorded as beats per minute. This recording was obtained at the same time the event marker on the Holter recorder was activated. This procedure ensured that HRV data coincided with heart rate data. Intrarater reliability for heart rate measures was r = 1.00, P<.001 on 10% of randomly selected ECG recordings. Respiratory Rate. Respiratory rate was determined by auscultation with a stethoscope over the chest wall for 30 seconds. This value was multiplied by 2 and recorded as breaths per minute. These measures were obtained once at each data collection point, immediately after the ECG recording was started and the event marker on the Holter recorder was activated. In order to ensure reliability of this measure, the same procedure was used at each data collection point, and only the investigator collected these measurements. Systolic Blood Pressure. Systolic blood pressure was obtained by using a noninvasive automatic oscillometric blood pressure cuff hard-wired to the cardiac monitoring system (Marquette Medical Systems, Milwaukee, Wis). In each subject, the left arm was used to collect all data on blood pressure. Furthermore, special attention was paid to determining the correct cuff size and to placing the sensor over the brachial artery. For each subject, the same-size cuff was used for all measurements. In order to obtain an oscillometric blood pressure, an electrical signal is generated in 1 circuit and processed in another. The first circuit amplifies and corrects the zero offset of the cuff pressure signal before the signal is digitized by the analog-to-digital converter. The second circuit filters and amplifies the raw cuff pressure signal to extract an amplified version of the cuff pressure oscillations. The autozero valve, which is in line with the pressure transducer pneumatics, opens the transducer to atmospheric pressure on a regular basis, enabling true zero pressure at the transducer. This zero pressure allows confident autozeroing of the pressure transducer and its associated circuitry.35 Automated oscillometric indirect measures correlate well (r = 0.91-0.99) with direct intra-arterial measures.36,37 Furthermore, less error is associated with automated oscillometric blood pressure devices than with auscultatory methods.38,39 According to studies on accuracy, the oscillometric method has a less than 5 mm Hg mean error with an SD of less than 8 mm Hg when compared with direct blood pressure measures.35 These variations fall within the standards for automated devices of the Association for the Advancement of Medical Instrumentation. Rate Pressure Product. Rate pressure product is calculated by multiplying heart rate by systolic blood pressure. It is a reliable noninvasive measure of myocardial oxygen demand.40,41 The methods described for obtaining heart rate and systolic blood pressure were used to gather data to complete this calculation. Heart Rate Variability. HRV was determined by using power spectral analysis and fast Fourier transform. Three hours of continuous ECG recording were collected by using a Holter recorder, and the data were analyzed in 6-minute epochs. In power spectral analysis, the natural oscillations of heart rate are broken down into their component frequencies, and the amplitude or power of each oscillation is plotted over a range of frequencies. On the basis of the resultant frequency components, inferences can be drawn about the influence of mental and physical activity, baroreceptors, and circadian rhythms.42-44 When power spectral analysis is used, the power of each contributing component is usually displayed over the frequency range of 0 to 0.5 Hz. When this manner of display is used, 3 primary frequencies of heart rate oscillations contain the majority of the heart power. The very low frequency band (0-0.04 Hz) is the least understood of the 3 regions and is thought to reflect thermoregulatory feedback mechanisms,45 renin-angiotensin activity,42 and circulating neurohormone levels.46 The low-frequency component (0.04-0.15 Hz) reflects both sympathetic and vagal input to the heart and the activity of chemoreceptors and baroreceptors.28,42,43,46-50 The origin of the high-frequency band (0.15-0.40 Hz) appears to be the parasympathetic nervous system exclusively.28,42,43,46-48,50 Rapid control of heart rate is effected through the balance of vagal (parasympathetic) and cardiac sympathetic fibers innervating the sinoatrial node. A reciprocal balance is maintained such that when one branch of the system is activated, the other is inhibited, and vice versa. For the purposes of this study, changes in the high-frequency band of the power spectrum were examined because the aim of the study was to improve cardiac autonomic balance, whereby vagal activity would be increased. For power spectral analysis, the ECG data were filtered, digitized, and passed through a fast Fourier transform. This process was accomplished by using a Laser SXP Ambulatory ECG Analysis and Editing System (Marquette Medical Systems Inc). The Laser SXP identified each ECG complex according to the morphology of the complex. This analysis was overread by the investigator to ensure correct identification of these complexes. Trend filtration was used to handle ectopy or data that could not be read.51 Each spectral output contains 128 bins, spanning the frequency range from 0 to 1.066 Hz. The trend filter compares each bin of a spectrum to the same frequency bin of the two adjacent 2-minute spectra. This median process removes singularity and treats ectopy and unidentifiable data as outliers. If a segment of nonsinus or bad data is long, trend filtration produces approximations that are excessively smooth, and the approximations tend to have lower variability than the surrounding segments of the time series. This practice tends to lower variability (total power) of the estimated spectrum, statistically biasing it to a lower value than it most likely should be. None of the tapes contained more than 5% unreadable or nonsinus complexes, and no 4-minute segments contained more than 5% nonsinus or unreadable complexes. In addition, reliability of HRV data was ensured by using intrarater reliability checks on 10% of the Holter tapes and subsequent HRV reanalyses. Anxiety. Anxiety was measured by using the state part of the State-Trait Anxiety Inventory. The state anxiety scale assesses feelings of apprehension, tension, nervousness, and worry as the feeling are experienced “right now.” Each of the 20 items that make up the scale is given a weighted score of 1 to 4. Anxiety scores are determined by adding the weighted scores for the 20 items. Scores can range from 20, indicating a low level of anxiety, to 80, reflecting a very high level. Uniformly high internal consistency levels have been shown with large, diverse samples. In this study, the a coefficient for the state scale, based on all 45 subjects, was .87. Results The typical subject was approximately 63 years old, male, white, married, and retired and had at least a high school education (Table 1). The 3 groups of subjects did not differ with respect to age (F2,42 = 1.17, P = .32), sex (X22 = 1.68, P = .43), ethnicity (X24 = 2.4, P = .66), educational level (X24 = 5.2, P = .27), or mean number of hours worked per week (F2,42 = 0.06, P = .95). All women in the study were postmenopausal, and none were being treated with estrogen replacement therapy. Although the groups differed in marital status (X22 = 6.96, P = .03), this difference most likely did not have any effect on outcomes. Therefore, this information was not used in any subsequent analysis of data. Five participants had a history of previous myocardial infarction (F2,42 = 1.24, P = .30). The 3 groups did not differ with respect to history of diabetes mellitus (X22 = 1.45, P = .48). x The 3 treatment groups were comparable at baseline. Types of current myocardial infarction were most commonly non–Q wave subendocardial (20%) and infarctions of the inferior (18%) and anterolateral (16%) walls. The groups did not differ with respect to use of fibrinolytic agents (F2,42 = 2.49, P = .09) or implementation of cardiac catheterization (X22 = 3.89, P = .14), percutaneous transluminal coronary angioplasty (c22 = 1.28, P = .53), or insertion of stents (X22 = 1.52, P = .47). All subjects were receiving pharmacological therapy. The groups did not differ in use of angiotensin-converting enzyme inhibitors (X22 = 0.55, P = .76), antiarrhythmic agents (X22 = 2.13, P = .35), or nitrates (X22 = 5.18, P = .07). Significantly more subjects (X22 = 10.13, P<.01) in the experimental (n = 11) and attention (n = 14) groups were taking ß-adrenergic blocking agents than those in the control group (n = 6). No subjects in the control group were receiving calcium channel blocking agents; 5 subjects in the attention group and 5 subjects in the experimental group were taking these medications. The control and experimental groups had 1 subject each who had cardiac glycosides prescribed; no one in the attention group was prescribed this type of medication. When differences among groups in use of ß-adrenergic blocking agents, calcium channel blocking agents, and cardiac glycosides were used as covariates in subsequent data analyses, outcomes were not affected significantly. I hypothesized that subjects who listened to relaxing music would have greater reductions in heart rate, respiratory rate, systolic blood pressure, myocardial oxygen demand, and state anxiety and greater increases in high-frequency HRV than subjects who experienced quiet rest or treatment as usual. I anticipated that these changes would occur immediately and 1 hour after the 20-minute intervention. Before a comparison of baseline variables was done, a correlation matrix was generated in an effort to detect multicollinearity among the dependent variables. Correlation coefficients ranged from r = –0.44 to r = 0.71. Because multicollinearity was not present, all dependent variables were included in subsequent analyses. No differences were found among groups for any of the dependent variables at baseline (Tables 2 and 3). x x In order to test the hypotheses, repeated measures multivariate analysis of variance (MANOVA) was done with all 6 dependent variables. When the results indicated a significant group-by-time interaction effect (F24,328 = 3.21, P<.001) for all 6 dependent variables, separate repeated measures MANOVAs were done in an effort to test the hypotheses for the individual dependent variables (Table 4). When significant group-by-time interaction effects were obtained, change scores were determined for dependent variables, and 1-way analyses of variances (ANOVAs) were done on these change scores (Table 5). Change scores were determined by subtracting measures of dependent variables obtained immediately after and 1 hour after the intervention from the values acquired at baseline. x x Group-by-time interaction effects for heart rate data with repeated measures MANOVA were not significant (F4,84 = 2.32, P = 0.06). However, the results of a Hotelling test for group-by-time interaction was significant (F4,80 = 2.55, P = .03). Therefore, 1-way ANOVAs were done on the scores for changes in heart rate. The results indicted a significant difference among groups immediately (F2,42 = 4.10, P = .02) and 1 hour (F2,42v=v3.46, P = .04) after the intervention. The results of Tukey honestly significantly difference (HSD) post hoc testing indicated that at both measurement points, reduction in heart rate was significantly greater for subjects who listened to music than for subjects who received treatment as usual. The attention group did not differ significantly from either the experimental or the control group with respect to changes in heart rate. A significant group-by-time interaction effect was found for respiratory rate (F4,84 = 5.25, P = .001. One-way ANOVAs for scores of changes in respiratory rate indicated a significant difference among groups immediately (F2,42 = 9.33, P<.001) and 1 hour (F2,42 = 4.62, P = .02) after the intervention. Tukey HSD post hoc testing revealed that the reduction in respiratory rate was significantly greater in the experimental group than in the control group at these measurement points. Again, according to post hoc testing, the attention group did not differ significantly from the control or the experimental group in changes in respiratory rate. The results of repeated measures MANOVA indicated a significant (F4,84 = 2.64, P = .04) group-by-time interaction effect for systolic blood pressure. However, according to 1-way ANOVA, changes in systolic blood pressure were not significant immediately or 1 hour after the intervention. Changes in myocardial oxygen demand were examined by using repeated measures MANOVA on rate pressure product data; the results indicated a significant (F4,84 = 2.71, Pv= .03) group-by-time interaction effect. One-way ANOVA of changes in rate pressure product revealed a significant difference among groups immediately after the intervention (F2,42 = 4.49, P = .01). The difference among groups 1 hour after the intervention was not significant (F2,42 = 2.11, P = .13). The results of Tukey HSD post hoc testing indicated that reduction in myocardial oxygen demand immediately after the intervention was significantly greater in the experimental group than in the control group. The attention group did not differ from either the control or the experimental group with respect to this variable. Similarly, repeated measures MANOVA disclosed a significant group-by-time interaction effect for high-frequency HRV data (F4,84 = 4.11, P = .004). The results of 1-way ANOVA indicated that differences were significant (F2,42 = 8.38, P<.001) for changes in high-frequency HRV immediately after the intervention but not for changes 1 hour later (F2,42 = 1.18, P = .32). According to Tukey HSD post hoc testing, increases in high-frequency HRV immediately after the intervention were significantly greater in both the attention and the experimental groups than in the control group. Finally, repeated measures MANOVAs indicated a significant group-by-time interaction effect for the data on anxiety (F4,84 = 10.09, P<.001). According to 1-way ANOVAs for changes in state anxiety among groups differed significant immediately (F2,42 = 12.65, P<.001) and 1 hour (F2,42 = 10.77, P<.001) after the intervention. According to Tukey HSD post hoc analysis, reduction in state anxiety scores immediately and 1 hour after the intervention was significantly greater in the experimental group than in the attention and the control groups. In summary, the 3 treatment groups were comparable at baseline in terms of demographic and baseline variables, with the exception of use of ß-adrenergic blocking agents, calcium channel blockers, and cardiac glycosides. As hypothesized, the experimental group had greater reductions in heart rate, respiratory rate, myocardial oxygen demand, and state anxiety scores immediately after the intervention period than did the control group. The reductions in heart rate and respiratory rate remained significant 1 hour after the intervention. Increases in high-frequency HRV immediately after the intervention were significantly greater in both the attention and the experimental groups than in the control groups. Although the repeated measures MANOVA for systolic blood pressure showed a significant group-by-time interaction effect, subsequent testing did not indicate a difference among groups. Statistical testing was repeated for heart rate, systolic blood pressure, myocardial oxygen demand, and high-frequency HRV, with use of ß-adrenergic blocking agents, calcium-channel blockers, and cardiac glycosides as covariates, and no significant changes in outcomes were noted. Discussion Admission to the hospital with the diagnosis of AMI can induce a stress response. This stress response manifests itself in many ways, including increased state anxiety. My results provide additional support for this phenomenon. Mean baseline state anxiety scores for participants in this study were 38.2 overall, 37.4 for men and 41.0 for women. These findings are consistent with those reported by others.6,8,11,52 According to these mean state anxiety scores, men were in approximately the 66th percentile and women in the 85th percentile for normal healthy adults in their respective age groups.34 These data provide compelling evidence of the magnitude of the psychological response to hospital admission after an AMI, and nurses must find effective interventions to combat the adverse effects that accompany admission. Music therapy may be an effective, inexpensive intervention to reduce anxiety and the accompanying adverse physiological effects. Results from this study and from previous studies provide supportive evidence for the usefulness of relaxing music in reducing state anxiety levels,6-7,9-11,53 heart rate,9-11 respiratory rate,11 and myocardial oxygen demand.53 No reports have been published of previous studies in which the effects of relaxing music on HRV were examined. Webster10 and Updike53 reported reductions in systolic blood pressure, results that are inconsistent with the findings from this study. The studies of both Webster10 and Updike53 had relatively small sample sizes. Of note, the pharmacological regimens after AMI in the early 1970s included fewer ß-adrenergic blocking agents than are used today. Furthermore, subjects in the Updike study included a variety of medical-surgical ICU patients, and no specific data were provided about the number of participants with AMI. Specific data on pharmacological agents were not provided in either of the studies. Because of the widespread use of cardiogenic medications in the participants in my study, the potential impact of these drugs on dependent variables must be considered. A variety of articles have addressed the possible effects of medications on HRV measures. Use of ß-adrenergic blocking agents can increase HRV in both healthy subjects and persons with cardiac disease.54-58 Use of angiotensin-converting enzyme inhibitors may also improve HRV59,60; the effects of calcium channel blockers have been inconsistent.61 Heart rate is reduced by ß-adrenergic blockers, calcium channel blockers, and cardiac glycosides, and ß-adrenergic blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors decrease blood pressure.62 Significantly more participants in the attention and experimental groups were taking ß-adrenergic blocking agents, whereas use of angiotensin-converting enzyme inhibitors was more prevalent in the control and attention groups. Only 2 subjects were taking cardiac glycosides, one in the control group, the other in the experimental group. These medications may have affected the measures of the dependent variables in this study. However, when differences in use of these medications were present across groups, they were used as covariates in subsequent analyses, and no significant changes in outcomes were noted. In this study, music therapy improved psychophysiological measures, and quiet, uninterrupted rest was associated with improvement in HRV. Previous studies11,12 also reported the physiological benefits of rest. Years ago, scheduled rest periods were commonplace in critical care units. Often, these rest periods were scheduled immediately after meals, because digestion places a significant burden on an already compromised myocardium. Use of scheduled rest periods may result in improved outcomes for patients. A substantial body of empirical evidence now indicates that relaxing music is beneficial to patients who have had an AMI. Previously completed studies with AMI patients do not indicate any adverse physiological effects from this type of musical experience. The time has come to make changes in practice. Libraries with a variety of relaxing music should be made available for patients’ use. In addition, further study is needed to determine optimal scheduling patterns and duration of music sessions. Testing the effects of the addition of music therapy to the normal ICU environment is also important. Whether adding sedate music to the busy ICU environment would promote a relaxation response or would act as an additional stimulus in an already arousing environment is not known. Most research on the effects of music therapy and AMI patients used classical music. The effectiveness of other types of music (eg, new age, jazz, easy listening), with components previously determined as most relaxing, requires empirical testing. Only if empirical evidence indicates that these types of music can elicit a relaxation response can clinicians prescribe other types of music with confidence. The long-term effects of implementing a program of music therapy as a strategy to reduce anxiety and stress require investigation. More than half of the participants in my study indicated that they thought they had a lot of stress in their lives. Of these patients, most had difficulty specifying any activities they routinely engaged in to reduce this stress. Music therapy would be an ideal intervention for AMI patients to use after discharge. Several participants in the study indicated that they were surprised by how good they felt after the music session. One patient shared that he never listened to music. He stated that he always listened to talk shows when he had the radio turned on. When this patient was visited the next day, a cassette recorder and cassette tapes were on his bedside table. He said that the music made him feel so good that he asked his wife to bring in some music for him. Likewise, another participant communicated that the music kept coming back to him and made him feel good. These positive responses indicate that patients recovering from AMI may be in a good position to learn about selecting appropriate music to assist them with relaxation after discharge. These findings provide evidence that ICU patients recovering from AMI may benefit when music therapy is provided in a quiet, low-stimulus, restful environment. In addition, quiet rest may improve HRV. With the current body of empirical evidence, critical care nurses can implement these interventions with confidence when caring for AMI patients. 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